Companies are continuously improving their practices and ways of working in order to fulfill always-changing market requirements. As an example of building a better understanding of their customers, organizations are collecting user feedback and trying to direct their R&D efforts by e.g. continuing to develop features that deliver value to the customer. We (1) develop an actionable technique that practitioners in organizations can use to validate feature value early in the development cycle, (2) validate if and when the expected value reflects on the customers, (3) know when to stop developing it, and (4) identity unexpected business value early during development and redirect R&D effort to capture this value. The technique has been validated in three experiments in two cases companies. Our findings show that predicting value for features under development helps product management in large organizations to correctly re-prioritize R&D investments.

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BibTeX @conference{Fabijan2015,author={Fabijan, A. and Olsson Holmström, Helena and Bosch, Jan},title={Early value argumentation and prediction: An iterative approach to quantifying feature value},booktitle={Lecture Notes in Computer Science. 16th International Conference on Product-Focused Software Process Improvement, PROFES 2015, Bolzano, Italy, 2-4 December 2015},isbn={978-3-319-26843-9},pages={16-23},abstract={Companies are continuously improving their practices and ways of working in order to fulfill always-changing market requirements. As an example of building a better understanding of their customers, organizations are collecting user feedback and trying to direct their R&D efforts by e.g. continuing to develop features that deliver value to the customer. We (1) develop an actionable technique that practitioners in organizations can use to validate feature value early in the development cycle, (2) validate if and when the expected value reflects on the customers, (3) know when to stop developing it, and (4) identity unexpected business value early during development and redirect R&D effort to capture this value. The technique has been validated in three experiments in two cases companies. Our findings show that predicting value for features under development helps product management in large organizations to correctly re-prioritize R&D investments.},year={2015},keywords={Continuous experimentation, Customer-driven development, Data-driven development, EVAP, QCD },}

RefWorks RT Conference ProceedingsSR ElectronicID 230838A1 Fabijan, A.A1 Olsson Holmström, HelenaA1 Bosch, JanT1 Early value argumentation and prediction: An iterative approach to quantifying feature valueYR 2015T2 Lecture Notes in Computer Science. 16th International Conference on Product-Focused Software Process Improvement, PROFES 2015, Bolzano, Italy, 2-4 December 2015SN 978-3-319-26843-9SP 16OP 23AB Companies are continuously improving their practices and ways of working in order to fulfill always-changing market requirements. As an example of building a better understanding of their customers, organizations are collecting user feedback and trying to direct their R&D efforts by e.g. continuing to develop features that deliver value to the customer. We (1) develop an actionable technique that practitioners in organizations can use to validate feature value early in the development cycle, (2) validate if and when the expected value reflects on the customers, (3) know when to stop developing it, and (4) identity unexpected business value early during development and redirect R&D effort to capture this value. The technique has been validated in three experiments in two cases companies. Our findings show that predicting value for features under development helps product management in large organizations to correctly re-prioritize R&D investments.LA engDO 10.1007/978-3-319-26844-6_2LK http://dx.doi.org/10.1007/978-3-319-26844-6_2OL 30